Integrated network analysis to identify the key genes, transcription factors, and microRNAs involved in hepatocellular carcinoma

Shu-Qing Shi, Jin-Jing Ke, Qi-Shun Xu, Wei-Quan Wu,  Yuan-Yu Wan

Abstract:

HCC (hepatocellular carcinoma), which can be induced by cirrhosis and viral hepatitis infection, is the most frequent form of liver cancer. This study is performed to investigate the mechanisms of HCC. GSE57957 was obtained from Gene Expression Omnibus database, including 39 HCC samples and 39 adjacent non-tumorous samples. The DEGs (differentially expressed genes) were screened using the limma package in R, and then were conducted with enrichment analysis using “BioCloud” platform. Using STRING database, WebGestalt tool, as well as ITFP and TRANSFAC databases, PPI (protein-protein interaction) pairs, miRNA (microRNA)-target pairs, and TF (transcription factor)-target pairs separately were predicted. Followed by integrated network was constructed by Cytoscape software and module analysis was performed using the MCODE plugin of Cytoscape software. There were 518 DEGs identified from the HCC samples, among which 17 up-regulated genes (including MCM2, MCM6, and CDC20) and 5 down-regulated genes could also function as TFs. In the integrated network for the down-regulated genes, FOS and ESR1 had higher degrees, and both of them were targeted by miR-221 and miR-222. Additionally, MCM2 had interaction with MCM6 in the up-regulated module with the highest score. MCM2, MCM6, CDC20, FOS, ESR1, miR-221 and miR-222 might affect the pathogenesis of HCC.